Automated Retinopathy of Prematurity Case Detection with Convolutional Neural Networks. - Daniel E. Worrall; Clare M. Wilson; Gabriel J. Brostow (LABELS/DLMIA@MICCAI, 2016)

Harmonic Networks: Deep Translation and Rotation Equivariance. - Daniel E. Worrall; Stephan J. Garbin; Daniyar Turmukhambetov; Gabriel J. Brostow (CVPR, 2017)

Interpretable Transformations with Encoder-Decoder Networks. - Daniel E. Worrall; Stephan J. Garbin; Daniyar Turmukhambetov; Gabriel J. Brostow (ICCV, 2017)

Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution. - Ryutaro Tanno; Daniel E. Worrall; Aurobrata Ghosh; Enrico Kaden; Stamatios N. Sotiropoulos; Antonio Criminisi; Daniel C. Alexander (MICCAI (1), 2017)

Virtual Adversarial Ladder Networks For Semi-supervised Learning. - Saki Shinoda; Daniel E. Worrall; Gabriel J. Brostow (CoRR, 2017)

CubeNet: Equivariance to 3D Rotation and Translation. - Daniel E. Worrall; Gabriel J. Brostow (ECCV (5), 2018)

Reversible GANs for Memory-Efficient Image-To-Image Translation. - Tycho F. A. van der Ouderaa; Daniel E. Worrall (CVPR, 2019)

Learning to Convolve: A Generalized Weight-Tying Approach. - Nichita Diaconu; Daniel E. Worrall (ICML, 2019)

Supervised Uncertainty Quantification for Segmentation with Multiple Annotations. - Shi Hu; Daniel E. Worrall; Stefan Knegt; Bas Veeling; Henkjan J. Huisman; Max Welling (MICCAI (2), 2019)

Deep Scale-spaces: Equivariance Over Scale. - Daniel E. Worrall; Max Welling (NeurIPS, 2019)

Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement. - Ryutaro Tanno; Daniel E. Worrall; Enrico Kaden; Aurobrata Ghosh; Francesco Grussu; Alberto Bizzi; Stamatios N. Sotiropoulos; Antonio Criminisi; Daniel C. Alexander (CoRR, 2019)

Affine Self Convolution. - Nichita Diaconu; Daniel E. Worrall (CoRR, 2019)

Learning Likelihoods with Conditional Normalizing Flows. - Christina Winkler; Daniel E. Worrall; Emiel Hoogeboom; Max Welling (CoRR, 2019)

Equivariance for deep learning and retinal imaging. - Daniel E. Worrall (2019)

SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks. - Fabian Fuchs; Daniel E. Worrall; Volker Fischer 003; Max Welling (NeurIPS, 2020)

MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning. - Elise van der Pol; Daniel E. Worrall; Herke van Hoof; Frans A. Oliehoek; Max Welling (NeurIPS, 2020)

Uncertainty modelling in deep learning for safer neuroimage enhancement: Demonstration in diffusion MRI. - Ryutaro Tanno; Daniel E. Worrall; Enrico Kaden; Aurobrata Ghosh; Francesco Grussu; Alberto Bizzi; Stamatios N. Sotiropoulos; Antonio Criminisi; Daniel C. Alexander (NeuroImage, 2021)

Learning Perturbations for Soft-Output Linear MIMO Demappers. - Daniel E. Worrall; Markus Peschl; Arash Behboodi; Roberto Bondesan (GLOBECOM, 2022)

Message Passing Neural PDE Solvers. - Johannes Brandstetter; Daniel E. Worrall; Max Welling (ICLR, 2022)

Lie Point Symmetry Data Augmentation for Neural PDE Solvers. - Johannes Brandstetter; Max Welling; Daniel E. Worrall (ICML, 2022)

Neural Simulated Annealing. - Alvaro H. C. Correia; Daniel E. Worrall; Roberto Bondesan (AISTATS, 2023)